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Empirical Ai
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Book Synopsis Empirical Methods for Artificial Intelligence by : Paul R. Cohen
Download or read book Empirical Methods for Artificial Intelligence written by Paul R. Cohen and published by Bradford Books. This book was released on 1995 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents empirical methods for studying complex computer programs: exploratory tools to help find patterns in data, experiment designs and hypothesis-testing tools to help data speak convincingly, and modeling tools to help explain data.
Book Synopsis Artificial Intelligence for a Better Future by : Bernd Carsten Stahl
Download or read book Artificial Intelligence for a Better Future written by Bernd Carsten Stahl and published by Springer Nature. This book was released on 2021-03-17 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book proposes a novel approach to Artificial Intelligence (AI) ethics. AI offers many advantages: better and faster medical diagnoses, improved business processes and efficiency, and the automation of boring work. But undesirable and ethically problematic consequences are possible too: biases and discrimination, breaches of privacy and security, and societal distortions such as unemployment, economic exploitation and weakened democratic processes. There is even a prospect, ultimately, of super-intelligent machines replacing humans. The key question, then, is: how can we benefit from AI while addressing its ethical problems? This book presents an innovative answer to the question by presenting a different perspective on AI and its ethical consequences. Instead of looking at individual AI techniques, applications or ethical issues, we can understand AI as a system of ecosystems, consisting of numerous interdependent technologies, applications and stakeholders. Developing this idea, the book explores how AI ecosystems can be shaped to foster human flourishing. Drawing on rich empirical insights and detailed conceptual analysis, it suggests practical measures to ensure that AI is used to make the world a better place.
Book Synopsis Empirical Inference by : Bernhard Schölkopf
Download or read book Empirical Inference written by Bernhard Schölkopf and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book honours the outstanding contributions of Vladimir Vapnik, a rare example of a scientist for whom the following statements hold true simultaneously: his work led to the inception of a new field of research, the theory of statistical learning and empirical inference; he has lived to see the field blossom; and he is still as active as ever. He started analyzing learning algorithms in the 1960s and he invented the first version of the generalized portrait algorithm. He later developed one of the most successful methods in machine learning, the support vector machine (SVM) – more than just an algorithm, this was a new approach to learning problems, pioneering the use of functional analysis and convex optimization in machine learning. Part I of this book contains three chapters describing and witnessing some of Vladimir Vapnik's contributions to science. In the first chapter, Léon Bottou discusses the seminal paper published in 1968 by Vapnik and Chervonenkis that lay the foundations of statistical learning theory, and the second chapter is an English-language translation of that original paper. In the third chapter, Alexey Chervonenkis presents a first-hand account of the early history of SVMs and valuable insights into the first steps in the development of the SVM in the framework of the generalised portrait method. The remaining chapters, by leading scientists in domains such as statistics, theoretical computer science, and mathematics, address substantial topics in the theory and practice of statistical learning theory, including SVMs and other kernel-based methods, boosting, PAC-Bayesian theory, online and transductive learning, loss functions, learnable function classes, notions of complexity for function classes, multitask learning, and hypothesis selection. These contributions include historical and context notes, short surveys, and comments on future research directions. This book will be of interest to researchers, engineers, and graduate students engaged with all aspects of statistical learning.
Book Synopsis Empirical Studies in Machine Psychology by : Robert Johansson
Download or read book Empirical Studies in Machine Psychology written by Robert Johansson and published by Linköping University Electronic Press. This book was released on 2024-10-09 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents Machine Psychology as an interdisciplinary paradigm that integrates learning psychology principles with an adaptive computer system for the development of Artificial General Intelligence (AGI). By synthesizing behavioral psychology with a formal intelligence model, the Non-Axiomatic Reasoning System (NARS), this work explores the potential of operant conditioning paradigms to advance AGI research. The thesis begins by introducing the conceptual foundations of Machine Psychology, detailing its alignment with the theoretical constructs of learning psychology and the formalism of NARS. It then progresses through a series of empirical studies designed to systematically investigate the emergence of increasingly complex cognitive behaviors as NARS interacts with its environment. Initially, operant conditioning is established as a foundational principle for developing adaptive behavior with NARS. Subsequent chapters explore increasingly sophisticated cognitive capabilities, all studied with NARS using experimental paradigms from operant learning psychology: Generalized identity matching, Functional equivalence, and Arbitrarily Applicable Relational Responding. Throughout this research, Machine Psychology is demonstrated to be a promising framework for guiding AGI research, allowing both the manipulation of environmental contingencies and the system’s intrinsic logical processes. The thesis contributes to AGI research by showing how using operant psychological paradigms with NARS can enable cognitive abilities similar to human cognition. These findings set the stage for AGI systems that learn and adapt more like humans, potentially advancing the creation of more general and flexible AI. Denna avhandling introducerar Maskinpsykologi som ett tvärvetenskapligt område där principer från inlärningspsykologi integreras med ett adaptivt datorsystem. Genom att kombinera forskning från beteendepsykologi med en formell modell för intelligens (Non-Axiomatic Reasoning System; NARS), undersöker avhandlingen hur operant betingning kan användas för att driva utvecklingen av Artificiell General Intelligens (AGI) framåt. Avhandlingen börjar med att förklara grunderna i Maskinpsykologi och hur dessa relaterar till både inlärningspsykologi och NARS. Därefter presenteras en serie experiment som systematiskt undersöker hur allt mer komplexa kognitiva beteenden kan uppstå när NARS interagerar med sin omgivning. Till att börja med etableras operant betingning som en central metod för att utveckla adaptiva beteenden med NARS. I de följande kapitlen utforskas hur NARS, genom experiment inspirerade av operant inlärningspsykologi, kan utveckla mer avancerade kognitiva förmågor som till exempel generaliserad identitetsmatchning, funktionell ekvivalens och så kallade arbiträrt applicerbara relationsresponser. Denna forskning visar att Maskinpsykologi är ett lovande verktyg för att vägleda AGI-forskning, eftersom det möjliggör att både påverka omgivningsfaktorer och styra systemets interna logiska processer. Avhandlingen bidrar till AGI-forskning genom att visa hur operanta psykologiska metoder, tillämpade på NARS, kan möjliggöra kognitiva förmågor som liknar mänskligt tänkande. Dessa insikter öppnar nya möjligheter för att utveckla AI-system som kan lära sig och anpassa sig på ett mer mänskligt sätt, vilket kan leda till skapandet av mer generell och flexibel AI.
Download or read book AI Magazine written by and published by . This book was released on 1998 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Foundations of Empirical Software Engineering by : Barry Boehm
Download or read book Foundations of Empirical Software Engineering written by Barry Boehm and published by Springer Science & Business Media. This book was released on 2005-05-13 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although software engineering can trace its beginnings to a NATO conf- ence in 1968, it cannot be said to have become an empirical science until the 1970s with the advent of the work of Prof. Victor Robert Basili of the University of Maryland. In addition to the need to engineer software was the need to understand software. Much like other sciences, such as physics, chemistry, and biology, software engineering needed a discipline of obs- vation, theory formation, experimentation, and feedback. By applying the scientific method to the software engineering domain, Basili developed concepts like the Goal-Question-Metric method, the Quality-Improvement- Paradigm, and the Experience Factory to help bring a sense of order to the ad hoc developments so prevalent in the software engineering field. On the occasion of Basili’s 65th birthday, we present this book c- taining reprints of 20 papers that defined much of his work. We divided the 20 papers into 6 sections, each describing a different facet of his work, and asked several individuals to write an introduction to each section. Instead of describing the scope of this book in this preface, we decided to let one of his papers, the keynote paper he gave at the International C- ference on Software Engineering in 1996 in Berlin, Germany to lead off this book. He, better than we, can best describe his views on what is - perimental software engineering.
Book Synopsis The Principles of Deep Learning Theory by : Daniel A. Roberts
Download or read book The Principles of Deep Learning Theory written by Daniel A. Roberts and published by Cambridge University Press. This book was released on 2022-05-26 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Book Synopsis Intelligent Systems by : André Britto
Download or read book Intelligent Systems written by André Britto and published by Springer Nature. This book was released on 2021-11-27 with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 13073 and 13074 constitutes the proceedings of the 10th Brazilian Conference on Intelligent Systems, BRACIS 2021, held in São Paolo, Brazil, in November-December 2021. The total of 77 papers presented in these two volumes was carefully reviewed and selected from 192 submissions.The contributions are organized in the following topical sections: Part I: Agent and Multi-Agent Systems, Planning and Reinforcement Learning; Evolutionary Computation, Metaheuristics, Constrains and Search, Combinatorial and Numerical Optimization, Knowledge Representation, Logic and Fuzzy Systems; Machine Learning and Data Mining. Part II: Multidisciplinary Artificial and Computational Intelligence and Applications; Neural Networks, Deep Learning and Computer Vision; Text Mining and Natural Language Processing. Due to the COVID-2019 pandemic, BRACIS 2021 was held as a virtual event.
Book Synopsis The Economics of Artificial Intelligence by : Ajay Agrawal
Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2024-03-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
Book Synopsis Generative AI for Effective Software Development by : Anh Nguyen-Duc
Download or read book Generative AI for Effective Software Development written by Anh Nguyen-Duc and published by Springer Nature. This book was released on with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Theoretical and Empirical Analysis in Environmental Economics by : Keiko Nakayama
Download or read book Theoretical and Empirical Analysis in Environmental Economics written by Keiko Nakayama and published by Springer. This book was released on 2019-05-17 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents potential remedies for some of the current environmental issues in developed countries in a theoretical or empirical manner with the interdisciplinary approaches of economics, statistics, and engineering. The book illustrates effective economic and environmental policies for environmental challenges and factors where corrective policies to date may have failed. The importance of this essential book has is related to the transition in the major concerns of the people or governments in developed countries shifting from economic growth to the stability of life and environmental preservation as their economies have matured. The environmental issues dealt with here include forest environment tax introduced as part of local taxes, air pollution reduction policies for mobile emission sources, introduction of renewable energies and power fuel cell technology, the mechanism of city agglomeration and dispersion, and measurement of environmental sustainability. In analytical methods, some research employs theoretical approaches such as the mathematical economic model or nonlinear dynamic model. Other analyses are implemented with empirical or statistical tools such as the long-run general equilibrium model, the input–output model, and the dynamic optimization model, among others.
Book Synopsis Empirical Approach to Machine Learning by : Plamen P. Angelov
Download or read book Empirical Approach to Machine Learning written by Plamen P. Angelov and published by Springer. This book was released on 2018-10-17 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a ‘one-stop source’ for all readers who are interested in a new, empirical approach to machine learning that, unlike traditional methods, successfully addresses the demands of today’s data-driven world. After an introduction to the fundamentals, the book discusses in depth anomaly detection, data partitioning and clustering, as well as classification and predictors. It describes classifiers of zero and first order, and the new, highly efficient and transparent deep rule-based classifiers, particularly highlighting their applications to image processing. Local optimality and stability conditions for the methods presented are formally derived and stated, while the software is also provided as supplemental, open-source material. The book will greatly benefit postgraduate students, researchers and practitioners dealing with advanced data processing, applied mathematicians, software developers of agent-oriented systems, and developers of embedded and real-time systems. It can also be used as a textbook for postgraduate coursework; for this purpose, a standalone set of lecture notes and corresponding lab session notes are available on the same website as the code. Dimitar Filev, Henry Ford Technical Fellow, Ford Motor Company, USA, and Member of the National Academy of Engineering, USA: “The book Empirical Approach to Machine Learning opens new horizons to automated and efficient data processing.” Paul J. Werbos, Inventor of the back-propagation method, USA: “I owe great thanks to Professor Plamen Angelov for making this important material available to the community just as I see great practical needs for it, in the new area of making real sense of high-speed data from the brain.” Chin-Teng Lin, Distinguished Professor at University of Technology Sydney, Australia: “This new book will set up a milestone for the modern intelligent systems.” Edward Tunstel, President of IEEE Systems, Man, Cybernetics Society, USA: “Empirical Approach to Machine Learning provides an insightful and visionary boost of progress in the evolution of computational learning capabilities yielding interpretable and transparent implementations.”
Book Synopsis Aspects of Artificial Intelligence by : J.H. Fetzer
Download or read book Aspects of Artificial Intelligence written by J.H. Fetzer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemological aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. The present volume illustrates the approach represented by this series. It addresses fundamental questions lying at the heart of artificial intelligence, including those of the relative virtues of computational and of non-computational conceptions of language and of mind, whether AI should be envisioned as a philosophical or as a scientific discipline, the theoretical character of patterns of inference and modes of argumenta tion (especially, defeasible and inductive reasoning), and the relations that may obtain between AI and epistemology. Alternative positions are developed in detail and subjected to vigorous debate in the justifiable expectation that - here as elsewhere - critical inquiry provides the most promising path to discovering the truth about ourselves and the world around us. lH.F.
Book Synopsis How to Lie with Statistics by : Darrell Huff
Download or read book How to Lie with Statistics written by Darrell Huff and published by W. W. Norton & Company. This book was released on 2010-12-07 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff’s lively and engaging primer clarifies the basic principles of statistics and explains how they’re used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.
Book Synopsis Disorganization Theory by : John Hassard
Download or read book Disorganization Theory written by John Hassard and published by Routledge. This book was released on 2007-10-04 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organizational analysis has moved in a number of directions since its origins in mainstream theories of positivism and functionalism. This challenging book sets out an alternative agenda for the field, discussing existing critical discourses, whilst exploring a selection of emerging ideas and arguments. Addressing a series of key epistemologic
Book Synopsis Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications by : Mina Farmanbar
Download or read book Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications written by Mina Farmanbar and published by Springer Nature. This book was released on with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Empirical Research on Semiotics and Visual Rhetoric by : Danesi, Marcel
Download or read book Empirical Research on Semiotics and Visual Rhetoric written by Danesi, Marcel and published by IGI Global. This book was released on 2018-02-23 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of symbols has long been considered a necessary field to unravel concealed meanings in symbols and images. These methods have since established themselves as staples in various fields of psychology, anthropology, computer science, and cognitive science. Empirical Research on Semiotics and Visual Rhetoric is a critical academic publication that examines communication through images and symbols and the methods by which researchers and scientists analyze these images and symbols. Featuring coverage on a wide range of topics, such as material culture, congruity theory, and social media, this publication is geared toward academicians, researchers, and students seeking current research on images, symbols, and how to analyze them.
